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International Conference on AI-driven Data Science in Genomics - (ICIADSG-27)

21st - 22nd May 2027 , Bristol - UK

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Call For Papers

The (ICIADSG-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Artificial Intelligence, Data Science, Machine Learning are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • AI applications in genomics data analysis
  • Machine learning for genetic variant interpretation
  • Data science for personalized medicine in genomics
  • AI-driven approaches to drug response prediction
  • Predictive analytics for disease risk assessment
  • Data privacy challenges in genomic research
  • AI for enhancing clinical genomics workflows
  • Machine learning in population genomics studies
  • AI applications in cancer genomics
  • Data visualization techniques for genomic data
  • AI for improving genetic counseling practices
  • Ethics in genomic data usage and AI
  • AI in rare disease research and treatment
  • Data-driven approaches to gene therapy development
  • AI for optimizing genomic sequencing technologies
  • Machine learning for epigenomics analysis
  • AI applications in microbiome research
  • Data science for evolutionary genomics studies
  • AI in pharmacogenomics and personalized therapy
  • Future trends in genomic AI research

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.

Submit Your Research Work Register Now